In latter years, there has been a growing interest in the possibility of being able to rapidly gather an overall picture of large amounts of data. This is due among other things to the increase of the data volumes in the society today and to the fact that nowadays it is possible to link different databases in an integrity-protected way. The traditional way of processing large data volumes is to strip information, step by step. For instance, database searches generally are carried out by initial selection of a specific geographical area, followed by selection of individuals of a specified age and income level, and so on, until only a manageable number of items remains.
For example, the U.S. Pat. Nos. 5,276,774, 5,377,348 and 5,136,523 disclose methods and devices for database searches. A feature common to all these publications is, however, that the user must begin by specifying the sought-after information, whereupon the search can be performed by matching the specified search data with the contents of the database, and the hits be presented to the user.
The disadvantage of this manner of processing data is, however, that the criteria of the search largely govern the search results, which is not very suitable when the target information of the search is not exactly clear from the start. In addition, it is difficult in a large database to be able to have an overall view of the data volume which would allow discovery of tendencies to co-variations of different parameters or trends and tendencies in time.
Some essential areas, such as environment, social economics, welfare development, publich health, commercial and industrial development and so on, cannot be understood from traditional measurements of individual variables, since by nature they involve a large number of different actors and a host of interacting variables within different dimensions. An understanding thereof may be achieved only if an overall view may be obtained as to how the total interplay between all these actors, variables and dimensions manifest themselves and result in co-variations, complex causal connections, development progress and patterns.
Generally speaking, coincidences in time and space may be referred to as events. The structure or processes affecting these events may be referred to as changes (forms of event) whereas the form of the changes, i.e. the manner and direction of these changes, may be an indication of the processes taking place in the mass of events. If several such processes move isomorphically, you have a pattern or a pattern-like behaviour. To search for such pattern-like changes in time in large data volumes is not possible by means of the solutions suggested in the above prior art.
In addition, by uniting databases there is an imminent risk that the identity of the objects will be revealed, which not only is unsatisfactory from the viewpoint of the individual's integrity but also results in many databases being restricted. In consequence thereof, the possibilities of linking databases are reduces as are the possibilities of implementing searches in such bases.